Snow tussocks, chaos, and the evolution of mast seeding

One hitherto intractable problem in studying mast seeding (synchronous intermittent heavy flowering by a population of perennial plants) is determining the relative roles of weather, plant reserves, and evolutionary selective pressures such as predator satiation. We parameterize a mechanistic resource-based model for mast seeding in Chionochloa pallens (Poaceae) using a long-term individually structured data set. Each plant's energy reserves were reconstructed using annual inputs (growing degree days), outputs (flowering), and a novel regression technique. This allowed the estimation of the parameters that control internal plant resource dynamics, and thereby allowed different models for masting to be tested against each other. Models based only on plant size, season degree days, and/or climatic cues (warm January temperatures) fail to reproduce the pattern of autocovariation in individual flowering and the high levels of flowering synchrony seen in the field. This shows that resource-matching or simple cue-based models cannot account for this example of mast seeding. In contrast, the resource-based model pulsed by a simple climate cue accurately describes both individual-level and population-level aspects of the data. The fitted resource-based model, in the absence of environmental forcing, has chaotic (but often statistically periodic) dynamics. Environmental forcing synchronizes individual reproduction, and the models predict highly variable seed production in close agreement with the data. An evolutionary model shows that the chaotic internal resource dynamics, as predicted by the fitted model, is selectively advantageous provided that adult mortality is low and seeds survive for more than 1 yr, both of which are true for C. pallens. Highly variable masting and chaotic dynamics appear to be advantageous in this case because they reduce seed losses to specialist seed predators, while balancing the costs of missed reproductive events

Modelling the impact of the environment on offshore wind turbine failure rates

For offshore wind turbines to become an economical energy generation option it is vital that the impact of the offshore environment on reliability is understood. This paper aims to model the impact of the wind speed and the external humidity and temperature. This is achieved using reliability data comprising of two modern, large scale wind farm sites consisting of approximately 380 wind turbine years of data. Weather data comes from a nearby weather station and an onsite met mast. A model is developed, using the reliability data, which calculates weather dependant failure rates and downtimes which are used to populate a Markov Chain. Monte Carlo simulation is then exercised to simulate the lifetime of a large scale wind farm which is subjected to controlled weather conditions. The model then calculates wind farm availability and component seasonal failure rates. Results show that offshore, the wind speed will have the biggest impact on component reliability, increasing the wind turbine failure rate by approximately 61%. The components affected most by this are the control system and the drive train. The higher offshore wind speeds appear to cause a higher proportion of major failures than experienced onshore. Research from this paper will be of interest to operators and wind turbine manufacturers who are interested in maintenance costs and logistics

The Multi-Application Survivable Tether (MAST) Experiment

Tethers Unlimited, Inc (TUI) and Stanford University’s Space Systems Development Laboratory (SSDL) are collaboratively developing the Multi-Application Survivable Tether (MAST) experiment, which will obtain data on tether performance, survivability, and dynamics. This data is crucial to the development of operational tether systems for propellantless propulsion and deorbit, formation-flying, and momentum-exchange transportation applications. The first objective of the MAST experiment is to obtain detailed on-orbit data on the survivability of space tethers and other gossamer spacecraft structures in the micrometeorite/orbital (M/OD) debris environment. The MAST experiment will deploy three 1-kg Cube- Sats along a 1-km Hoytether that incorporates both conducting and nonconducting materials. The middle CubeSat will then slowly translate along the tether, inspecting the tether as it moves and returning data on the rate of damage to the tether by M/OD impacts. The second objective of the experiment will be to study the dynamics of tethered formations of spacecraft and rotating tether systems. This data is required to enable the validation of space tether simulation tools such as TetherSim and GTOSS. The third objective of the experiment will be to demonstrate momentum-exchange tether concepts. In this paper we will present results of initial design studies and analyses of MAST system dynamics and performance

A CFD technique for estimating the flow distortion effects on LiDAR measurements when made in complex flow fields

The effect of flow distortion on the measurements produced by a LiDAR or SoDAR in close proximity to either complex terrain or a structure creating localised flow distortion is difficult to determine by analytical means. Also, as LiDARs and SoDARs are not point measurement devices, the techniques they employ for velocity measurements leads to complexities in the estimation of the effect of flow distortion on the accuracy of the measurements they make. This paper presents a method by which the effect of flow distortion on measurements made by a LiDAR in a distorted flow field may be determined using computational fluid dynamics. The results show that the error created by the flow distortion will cause the vector measured by a LiDAR to differ significantly from an equivalent point measurement. However, the results of the simulation show that, if the LiDAR is being used to measure the undisturbed flow field above a structure which creates highly localised flow distortion, the LiDAR results are less affected by the distortion of the local flow field than data acquired by a point measurement technique such as a cup anemometer

Evaluating single-sided natural ventilation models against full-scale idealised measurements: impact of wind direction and turbulence

Commonly single-sided natural ventilation is used in temperate climates to provide comfortable and healthy indoor environments. However, within built-up areas it is difficult to predict natural ventilation rates for buildings as they depend on many flow factors and opening type. Here, existing models are evaluated using the nine-month Refresh Cube Campaign (RCC). Pressure-based ventilation rates were determined for a small opening (1% porosity) in a cubical test building (side=6 m). The building was isolated and then sheltered in a limited staggered building array to simulate turbulent flows in dense urban areas. Internal and external flow, temperature and pressure measurements captured a wide range of scales of variability. Although the Warren and Parkins (1985, WP85) model performed best for 30-minute mean ventilation rates, all four models tested underestimated ventilation rates by a factor of 10. As wind dominated the stack effect, new coefficients were derived for the WP85 wind-driven model as a function of wind angle. Predictions were mostly improved, except for directions with complex flow patterns during the sheltered case. For the first time, the relation between ventilation rate and turbulence intensity (TI) around a full-scale building was tested. Results indicate that the wind-driven model for single-sided ventilation in highly turbulent flows (0.5<TI<4) can be improved by including TI as a multiplicative factor. Although small window openings with highly turbulent flows are common for sheltered buildings in urban areas, future model development should include a variety of configurations to assess the generality of these results

Endogenous and exogenous constraints in the population changes of wild boar (sus scrofa Linnaeus, 1758)

The population dynamics of wild boar (Sus scrofa) was studied in a time series over 26 years using data from the Regional Hunting Reserve of Somiedo (northern Spain). This population is controlled by a complex negative feedback system that acts with one (main) and two (secondary) years of delay (lags). The primary feedback might be explained by intraspecific competition for food resulting from fluctuations in mast production (acorns and beech), and the secondary feedback might be explained by the influence of weather conditions or the delay of a cohort to reach reproductive status. We used a stochastic model that takes environmental variability into consideration when testing the demographical analysis that’s obtains simulations from real data

Controlled multibody dynamics simulation for large space structures

Multibody dynamics discipline, and dynamic simulation in control structure interaction (CSI) design are discussed. The use, capabilities, and architecture of the Large Angle Transient Dynamics (LATDYN) code as a simulation tool are explained. A generic joint body with various types of hinge connections; finite element and element coordinate systems; results of a flexible beam spin-up on a plane; mini-mast deployment; space crane and robotic slewing manipulations; a potential CSI test article; and multibody benchmark experiments are also described